31 research outputs found

    Event-Driven Technologies for Reactive Motion Planning: Neuromorphic Stereo Vision and Robot Path Planning and Their Application on Parallel Hardware

    Get PDF
    Die Robotik wird immer mehr zu einem Schlüsselfaktor des technischen Aufschwungs. Trotz beeindruckender Fortschritte in den letzten Jahrzehnten, übertreffen Gehirne von Säugetieren in den Bereichen Sehen und Bewegungsplanung noch immer selbst die leistungsfähigsten Maschinen. Industrieroboter sind sehr schnell und präzise, aber ihre Planungsalgorithmen sind in hochdynamischen Umgebungen, wie sie für die Mensch-Roboter-Kollaboration (MRK) erforderlich sind, nicht leistungsfähig genug. Ohne schnelle und adaptive Bewegungsplanung kann sichere MRK nicht garantiert werden. Neuromorphe Technologien, einschließlich visueller Sensoren und Hardware-Chips, arbeiten asynchron und verarbeiten so raum-zeitliche Informationen sehr effizient. Insbesondere ereignisbasierte visuelle Sensoren sind konventionellen, synchronen Kameras bei vielen Anwendungen bereits überlegen. Daher haben ereignisbasierte Methoden ein großes Potenzial, schnellere und energieeffizientere Algorithmen zur Bewegungssteuerung in der MRK zu ermöglichen. In dieser Arbeit wird ein Ansatz zur flexiblen reaktiven Bewegungssteuerung eines Roboterarms vorgestellt. Dabei wird die Exterozeption durch ereignisbasiertes Stereosehen erreicht und die Pfadplanung ist in einer neuronalen Repräsentation des Konfigurationsraums implementiert. Die Multiview-3D-Rekonstruktion wird durch eine qualitative Analyse in Simulation evaluiert und auf ein Stereo-System ereignisbasierter Kameras übertragen. Zur Evaluierung der reaktiven kollisionsfreien Online-Planung wird ein Demonstrator mit einem industriellen Roboter genutzt. Dieser wird auch für eine vergleichende Studie zu sample-basierten Planern verwendet. Ergänzt wird dies durch einen Benchmark von parallelen Hardwarelösungen wozu als Testszenario Bahnplanung in der Robotik gewählt wurde. Die Ergebnisse zeigen, dass die vorgeschlagenen neuronalen Lösungen einen effektiven Weg zur Realisierung einer Robotersteuerung für dynamische Szenarien darstellen. Diese Arbeit schafft eine Grundlage für neuronale Lösungen bei adaptiven Fertigungsprozesse, auch in Zusammenarbeit mit dem Menschen, ohne Einbußen bei Geschwindigkeit und Sicherheit. Damit ebnet sie den Weg für die Integration von dem Gehirn nachempfundener Hardware und Algorithmen in die Industrierobotik und MRK

    Reasoning and understanding grasp affordances for robot manipulation

    Get PDF
    This doctoral research focuses on developing new methods that enable an artificial agent to grasp and manipulate objects autonomously. More specifically, we are using the concept of affordances to learn and generalise robot grasping and manipulation techniques. [75] defined affordances as the ability of an agent to perform a certain action with an object in a given environment. In robotics, affordances defines the possibility of an agent to perform actions with an object. Therefore, by understanding the relation between actions, objects and the effect of these actions, the agent understands the task at hand, providing the robot with the potential to bridge perception to action. The significance of affordances in robotics has been studied from varied perspectives, such as psychology and cognitive sciences. Many efforts have been made to pragmatically employ the concept of affordances as it provides the potential for an artificial agent to perform tasks autonomously. We start by reviewing and finding common ground amongst different strategies that use affordances for robotic tasks. We build on the identified grounds to provide guidance on including the concept of affordances as a medium to boost autonomy for an artificial agent. To this end, we outline common design choices to build an affordance relation; and their implications on the generalisation capabilities of the agent when facing previously unseen scenarios. Based on our exhaustive review, we conclude that prior research on object affordance detection is effective, however, among others, it has the following technical gaps: (i) the methods are limited to a single object ↔ affordance hypothesis, and (ii) they cannot guarantee task completion or any level of performance for the manipulation task alone nor (iii) in collaboration with other agents. In this research thesis, we propose solutions to these technical challenges. In an incremental fashion, we start by addressing the limited generalisation capabilities of, at the time state-of-the-art methods, by strengthening the perception to action connection through the construction of an Knowledge Base (KB). We then leverage the information encapsulated in the KB to design and implement a reasoning and understanding method based on statistical relational leaner (SRL) that allows us to cope with uncertainty in testing environments, and thus, improve generalisation capabilities in affordance-aware manipulation tasks. The KB in conjunctions with our SRL are the base for our designed solutions that guarantee task completion when the robot is performing a task alone as well as when in collaboration with other agents. We finally expose and discuss a range of interesting avenues that have the potential to thrive the capabilities of a robotic agent through the use of the concept of affordances for manipulation tasks. A summary of the contributions of this thesis can be found at: https://bit.ly/grasp_affordance_reasonin

    Social and Affective Neuroscience of Everyday Human Interaction

    Get PDF
    This Open Access book presents the current state of the art knowledge on social and affective neuroscience based on empirical findings. This volume is divided into several sections first guiding the reader through important theoretical topics within affective neuroscience, social neuroscience and moral emotions, and clinical neuroscience. Each chapter addresses everyday social interactions and various aspects of social interactions from a different angle taking the reader on a diverse journey. The last section of the book is of methodological nature. Basic information is presented for the reader to learn about common methodologies used in neuroscience alongside advanced input to deepen the understanding and usability of these methods in social and affective neuroscience for more experienced readers

    Social and Affective Neuroscience of Embodiment

    Get PDF
    Embodiment has been discussed in the context of social, affective, and cognitive psychology, and also in the investigations of neuroscience in order to understand the relationship between biological mechanisms, body and cognitive, and social and affective processes. New theoretical models have been presented by researchers considering not only the sensory–motor interaction and the environment but also biological mechanisms regulating homeostasis and neural processes (Tsakiris M, Q J Exp Psychol 70(4):597–609, 2017). Historically, the body and the mind were comprehended as separate entities. The body was considered to function as a machine, responsible for providing sensory information to the mind and executing its commands. The mind, however, would process information in an isolated way, similar to a computer (Pecher D, Zwaan RA, Grounding cognition: the role of perception and action in memory, language, and thinking. Cambridge University Press, 2005). This mind and body perspective (Marmeleira J, Duarte Santos G, Percept Motor Skills 126, 2019; Marshall PJ, Child Dev Perspect 10(4):245–250, 2016), for many years, was the basis for studies in social and cognitive areas, in neuroscience, and clinical psychology

    Facial EMG – Investigating the Interplay of Facial Muscles and Emotions

    Get PDF
    This chapter provides information about facial electromyography (EMG) as a method of investigating emotions and affect, including examples of application and methods for analysis. This chapter begins with a short introduction to emotion theory followed by an operationalisation of facial emotional expressions as an underlying requirement for their study using facial EMG. This chapter ends by providing practical information on the use of facial EMG

    Advances in Human-Robot Interaction

    Get PDF
    Rapid advances in the field of robotics have made it possible to use robots not just in industrial automation but also in entertainment, rehabilitation, and home service. Since robots will likely affect many aspects of human existence, fundamental questions of human-robot interaction must be formulated and, if at all possible, resolved. Some of these questions are addressed in this collection of papers by leading HRI researchers

    Human Inspired Multi-Modal Robot Touch

    Get PDF

    Mobile Robots Navigation

    Get PDF
    Mobile robots navigation includes different interrelated activities: (i) perception, as obtaining and interpreting sensory information; (ii) exploration, as the strategy that guides the robot to select the next direction to go; (iii) mapping, involving the construction of a spatial representation by using the sensory information perceived; (iv) localization, as the strategy to estimate the robot position within the spatial map; (v) path planning, as the strategy to find a path towards a goal location being optimal or not; and (vi) path execution, where motor actions are determined and adapted to environmental changes. The book addresses those activities by integrating results from the research work of several authors all over the world. Research cases are documented in 32 chapters organized within 7 categories next described

    On the Use of Large Area Tactile Feedback for Contact Data Processing and Robot Control

    Get PDF
    The progress in microelectronics and embedded systems has recently enabled the realization of devices for robots functionally similar to the human skin, providing large area tactile feedback over the whole robot body. The availability of such kind of systems, commonly referred to as extit{robot skins}, makes possible to measure the contact pressure distribution applied on the robot body over an arbitrary area. Large area tactile systems open new scenarios on contact processing, both for control and cognitive level processing, enabling the interpretation of physical contacts. The contents proposed in this thesis address these topics by proposing techniques exploiting large area tactile feedback for: (i) contact data processing and classification; (ii) robot control
    corecore